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Using structure prediction of negative sense RNA virus nucleoproteins to assess evolutionary relationships
Open accessPublished version of a preprint
Abstract
Negative sense RNA viruses (NSV) include some of the most detrimental human pathogens, including the influenza, Ebola, and measles viruses. NSV genomes consist of one or multiple single-stranded RNA molecules that are encapsidated into one or more ribonucleoprotein (RNP) complexes. These RNPs consist of viral RNA, a viral RNA polymerase, and many copies of the viral nucleoprotein (NP). Current evolutionary relationships within the NSV phylum are based on the alignment of conserved RNA-dependent RNA polymerase (RdRp) domain amino acid sequences. However, the RdRp domain-based phylogeny does not address whether NP, the other core protein in the NSV genome, evolved along the same trajectory or whether several RdRp–NP pairs evolved through convergent evolution in the segmented and non-segmented NSV genome architectures. Addressing how NP and the RdRp domain evolved may help us better understand NSV diversity. Since NP sequences are too short to infer robust phylogenetic relationships, we here used experimentally obtained and AlphaFold 2.0-predicted NP structures to probe whether evolutionary relationships can be estimated using NSV NP sequences. Following flexible structure alignments of modeled structures, we find that the structural homology of the NSV NPs reveals phylogenetic clusters that are consistent with RdRp-based clustering. In addition, we were able to assign viruses for which RdRp sequences are currently missing to phylogenetic clusters based on the available NP sequence. Both our RdRp-based and NP-based relationships deviate from the current NSV classification of the segmented Naedrevirales, which cluster with the other segmented NSVs in our analysis. Overall, our results suggest that the NSV RdRp and NP genes largely evolved along similar trajectories and even short pieces of genetic, protein-coding information can be used to infer evolutionary relationships, potentially making metagenomic analyses more valuable.
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Cites
Highly accurate protein structure prediction with AlphaFold
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Metadata
- Authors
- Sabsay, K. R., & te Velthuis, A. J. W.
- Affiliations
- Princeton University (US)
- Lewis Thomas Laboratory, Department of Molecular Biology, Princeton University , Washington Road, Princeton, NJ 08544, United States
- Venue
- Virus Evolution
- Publisher
- Oxford University Press (OUP)
- Published
- 2024
- Volume
- 10
- Issue
- 1
- Pages
- veae058-veae058
- ISSN
- 2057-1577 (ISSN-L)
- PMC
- PMC11315766
- OpenAlex
- W4401040921
- Cited by
- 3
- References
- 3
- Citations by year
- 2026: 1 · 2024: 2
- FWCI
- 0.92
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Virus Evolution (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion, cc-by)
- Funders
- Division of Microbiology and Infectious Diseases (DP2 AI175474 R01 AI170520)
- Wellcome Trust (206579/17/Z)
- Topics
- Health Sciences › Medicine › Epidemiology › Virology and Viral Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- negative-sense RNA viruses, viral nucleoprotein, RNA-dependent RNA polymerase, viral evolution, phylogenetic relationships, protein structure prediction, AlphaFold, structural homology, convergent evolution, ribonucleoprotein, metagenomics
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